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Article
Publication date: 29 October 2019

Mohammad Muzzammil Zekri and Muhammad Najib Razali

This paper aims to examine the dynamic of volatility of Malaysian listed property companies within pan-Asian public property markets based on different volatility…

Abstract

Purpose

This paper aims to examine the dynamic of volatility of Malaysian listed property companies within pan-Asian public property markets based on different volatility perspective over the past 18 years, especially during the global financial crisis (GFC).

Design/methodology/approach

This study uses several statistical methods and formulas for analysing the dynamic of volatility of Malaysian listed property companies such as exponential generalised autoregressive conditional heteroscedasticity (EGARCH) and Markov-switching (MS) EGARCH. The MS-EGARCH model provides new insights on the volatility dynamics of Malaysian listed property companies compared to conventional volatility modelling techniques, particularly EGARCH. Additionally, this paper will analyse the volatility movement based on three different sub-periods such as pre-GFC, GFC and post-GFC.

Findings

The findings reveal that the markets perform differently under different volatility conditions. Moreover, the application of MS-EGARCH provides a different view on the volatility dynamics compared to the conventional EGARCH model, as MS-EGARCH provides more comprehensive findings, especially during extreme market conditions.

Originality/value

This study contributes to the literature on the dynamics of Malaysian listed property companies within pan-Asian countries, as the approach for assessing the volatility performance based on different volatility conditions is less explored by previous researchers.

Details

Journal of Financial Management of Property and Construction , vol. 25 no. 1
Type: Research Article
ISSN: 1366-4387

Keywords

Article
Publication date: 7 August 2009

Chyi Lin Lee

The purpose of this paper is to examine the housing price volatility for eight capital cities in Australia over 1987‐2007. Specifically, the volatility of Australian…

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Abstract

Purpose

The purpose of this paper is to examine the housing price volatility for eight capital cities in Australia over 1987‐2007. Specifically, the volatility of Australian housing and its determinants were investigated.

Design/methodology/approach

An exponential‐generalised autoregressive conditional heteoskedasticity (EGARCH) model was employed to analyse the volatility for eight capital cities in Australia. The Engle LM test was also utilised to examine the volatility clustering effects in these cities.

Findings

The volatility clustering effects (ARCH effects) were found in many Australian capital cities. The importance of estimating each individual city's EGARCH model was also demonstrated in which the determinants of housing volatility vary from a city to another city. Asymmetric of the positive and negative shocks were also documented.

Research limitations/implications

This study has implications for investors and policy makers in which housing investors should estimate the conditional variance (EGARCH process) of a housing market in respect to the volatility of housing series is not always constant over time. Furthermore, policy makers should also address the importance of considering the sub‐national factors in formulating the national housing policy. The analysis and results are limited by the quality of the data.

Originality/value

This paper is one of the few studies in housing volatility. Additionally, it is probably the first attempt to assess the volatility spillover effects in the Australian housing market.

Details

International Journal of Housing Markets and Analysis, vol. 2 no. 3
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 25 May 2010

Alok Dixit, Surendra S. Yadav and P.K. Jain

The purpose of this paper is to assess the informational efficiency of S&P CNX Nifty index options in Indian securities market. The S&P CNX Nifty index is a leading stock…

Abstract

Purpose

The purpose of this paper is to assess the informational efficiency of S&P CNX Nifty index options in Indian securities market. The S&P CNX Nifty index is a leading stock index of India, consists of 50 most frequently traded securities listed on NSE. For the purpose, the study covers a period of six years from 4 June 2001 (the starting date for index options in India) to 30 June 2007.

Design/methodology/approach

The informational efficiency of implied volatilities (IVs) has been tested vis‐à‐vis select conditional volatilities models, namely, GARCH(1,1) and EGARCH(1,1). The tests have been carried out for “in‐the‐sample” as well as “out‐of‐the‐sample” forecast efficiency of implied volatilities.

Findings

The results of the study reveal that implied volatilities do not impound all the information available in the past returns; therefore, these are indicative of the violation of efficient market hypothesis in the case of S&P CNX Nifty index options market in India.

Practical implications

The finance managers, in Indian context, should rely on conditional volatility models (especially the EGARCH(1,1) model) compared to IV‐based forecasts to predict volatility for the horizon of one week. The stock exchanges and market regulator (SEBI) need to take certain initiatives in terms of extending the short‐selling facility and start trading of volatility index (VIX) to enhance the accuracy of IV‐based forecasts.

Originality/value

The paper addresses an issue which is still unexplored in the context of Indian securities market and in that sense makes an important contribution to literature on microstructure studies.

Details

Journal of Advances in Management Research, vol. 7 no. 1
Type: Research Article
ISSN: 0972-7981

Keywords

Article
Publication date: 4 May 2012

Gregory Koutmos

This paper aims to propose a general, yet simple model to estimate interest rate volatility.

1043

Abstract

Purpose

This paper aims to propose a general, yet simple model to estimate interest rate volatility.

Design/methodology/approach

The methodology is based on an extended Exponential Generalized ARCH (EGARCH) model that incorporates both interest rate levels as well as past information shocks in the volatility function. More importantly, the model is log‐linear thus eliminating collinearity problems and it can be easily estimated using standard maximum likelihood techniques.

Findings

The empirical evidence suggests that the elasticity of volatility to the level of interest rates, although statistically significant, is not as high numerically as previously thought. In fact innovations in the interest rate process are more significant than the level of interest rates. The most important feature of interest rates, however, is the high volatility persistence.

Research limitations/implications

A limitation of the model is that it does not allow for structural shifts in its current form. Extending the model to accommodate possible shifts would probably improve the performance as well the forecasting accuracy.

Practical implications

The findings in this paper have important implications for the accurate pricing of fixed income derivative securities as well as the efficient risk management of fixed income portfolios.

Originality/value

The paper provides a convenient and unifying methodological framework for assessing the importance and forecasting ability of the various volatility components.

Details

Managerial Finance, vol. 38 no. 6
Type: Research Article
ISSN: 0307-4358

Keywords

Article
Publication date: 10 May 2018

Dimitrios Kyrkilis, Athanasios Koulakiotis, Vassilios Babalos and Maria Kyriakou

The purpose of this paper is to examine the hypothesis of feedback trading along with the short-term return dynamics of three size-based stock portfolios of Athens Stock…

Abstract

Purpose

The purpose of this paper is to examine the hypothesis of feedback trading along with the short-term return dynamics of three size-based stock portfolios of Athens Stock Exchange during the Greek debt crisis period.

Design/methodology/approach

To this end, the authors employ for the first time in the literature two well-known models while the variance equation is modeled by means of a multivariate EGARCH specification. As a robustness test an innovative nested-EGARCH model is also employed.

Findings

The assumption that positive feedback trading is an important component of the short-term return movements across the three stock portfolios receives significant support. Moreover, the volatility interdependence, both in magnitude and sign, is almost similar across the three models. Finally, bad news originating from the portfolio of small stock appears to have a higher impact on the volatility of large and medium size stock returns than good news during the Greek debt crisis period.

Originality/value

The methodology is innovative and the authors test for the first time the feedback trading hypothesis across different size stocks. The authors believe that the results might entail significant policy implications for investors and market regulators.

Details

International Journal of Managerial Finance, vol. 14 no. 5
Type: Research Article
ISSN: 1743-9132

Keywords

Book part
Publication date: 21 November 2014

Chi Wan and Zhijie Xiao

This paper analyzes the roles of idiosyncratic risk and firm-level conditional skewness in determining cross-sectional returns. It is shown that the traditional EGARCH

Abstract

This paper analyzes the roles of idiosyncratic risk and firm-level conditional skewness in determining cross-sectional returns. It is shown that the traditional EGARCH estimates of conditional idiosyncratic volatility may bring significant finite sample estimation bias in the presence of non-Gaussianity. We propose a new estimator that has more robust sampling performance than the EGARCH MLE in the presence of heavy-tail or skewed innovations. Our cross-sectional portfolio analysis demonstrates that the idiosyncratic volatility puzzle documented by Ang, Hodrick, Xiang, and Zhang (2006) exists intertemporally. We conduct further analysis to solve the puzzle. We show that two factors idiosyncratic variance and individual conditional skewness play important roles in determining cross-sectional returns. A new concept, the “expected windfall,” is introduced as an alternate measure of conditional return skewness. After controlling for these two additional factors, we solve the major piece of this puzzle: Our cross-sectional regression tests identify a positive relationship between conditional idiosyncratic volatility and expected returns for over 99% of the total market capitalization of the NYSE, NASDAQ, and AMEX stock exchanges.

Details

Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

Keywords

Book part
Publication date: 19 November 2014

Garland Durham and John Geweke

Massively parallel desktop computing capabilities now well within the reach of individual academics modify the environment for posterior simulation in fundamental and…

Abstract

Massively parallel desktop computing capabilities now well within the reach of individual academics modify the environment for posterior simulation in fundamental and potentially quite advantageous ways. But to fully exploit these benefits algorithms that conform to parallel computing environments are needed. This paper presents a sequential posterior simulator designed to operate efficiently in this context. The simulator makes fewer analytical and programming demands on investigators, and is faster, more reliable, and more complete than conventional posterior simulators. The paper extends existing sequential Monte Carlo methods and theory to provide a thorough and practical foundation for sequential posterior simulation that is well suited to massively parallel computing environments. It provides detailed recommendations on implementation, yielding an algorithm that requires only code for simulation from the prior and evaluation of prior and data densities and works well in a variety of applications representative of serious empirical work in economics and finance. The algorithm facilitates Bayesian model comparison by producing marginal likelihood approximations of unprecedented accuracy as an incidental by-product, is robust to pathological posterior distributions, and provides estimates of numerical standard error and relative numerical efficiency intrinsically. The paper concludes with an application that illustrates the potential of these simulators for applied Bayesian inference.

Open Access
Article
Publication date: 11 April 2021

Josephine Dufitinema

The purpose of this paper is to compare different models’ performance in modelling and forecasting the Finnish house price returns and volatility.

Abstract

Purpose

The purpose of this paper is to compare different models’ performance in modelling and forecasting the Finnish house price returns and volatility.

Design/methodology/approach

The competing models are the autoregressive moving average (ARMA) model and autoregressive fractional integrated moving average (ARFIMA) model for house price returns. For house price volatility, the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model is competing with the fractional integrated GARCH (FIGARCH) and component GARCH (CGARCH) models.

Findings

Results reveal that, for modelling Finnish house price returns, the data set under study drives the performance of ARMA or ARFIMA model. The EGARCH model stands as the leading model for Finnish house price volatility modelling. The long memory models (ARFIMA, CGARCH and FIGARCH) provide superior out-of-sample forecasts for house price returns and volatility; they outperform their short memory counterparts in most regions. Additionally, the models’ in-sample fit performances vary from region to region, while in some areas, the models manifest a geographical pattern in their out-of-sample forecasting performances.

Research limitations/implications

The research results have vital implications, namely, portfolio allocation, investment risk assessment and decision-making.

Originality/value

To the best of the author’s knowledge, for Finland, there has yet to be empirical forecasting of either house price returns or/and volatility. Therefore, this study aims to bridge that gap by comparing different models’ performance in modelling, as well as forecasting the house price returns and volatility of the studied market.

Details

International Journal of Housing Markets and Analysis, vol. 15 no. 1
Type: Research Article
ISSN: 1753-8270

Keywords

Open Access
Article
Publication date: 12 June 2017

Nara Rossetti, Marcelo Seido Nagano and Jorge Luis Faria Meirelles

This paper aims to analyse the volatility of the fixed income market from 11 countries (Brazil, Russia, India, China, South Africa, Argentina, Chile, Mexico, USA, Germany…

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Abstract

Purpose

This paper aims to analyse the volatility of the fixed income market from 11 countries (Brazil, Russia, India, China, South Africa, Argentina, Chile, Mexico, USA, Germany and Japan) from January 2000 to December 2011 by examining the interbank interest rates from each market.

Design/methodology/approach

To the volatility of interest rates returns, the study used models of auto-regressive conditional heteroscedasticity, autoregressive conditional heteroscedasticity (ARCH), generalized autoregressive conditional heteroscedasticity (GARCH), exponential generalized autoregressive conditional heteroscedasticity (EGARCH), threshold generalized autoregressive conditional heteroscedasticity (TGARCH) and periodic generalized autoregressive conditional heteroscedasticity (PGARCH), and a combination of these with autoregressive integrated moving average (ARIMA) models, checking which of these processes were more efficient in capturing volatility of interest rates of each of the sample countries.

Findings

The results suggest that for most markets, studied volatility is best modelled by asymmetric GARCH processes – in this case the EGARCH – demonstrating that bad news leads to a higher increase in the volatility of these markets than good news. In addition, the causes of increased volatility seem to be more associated with events occurring internally in each country, as changes in macroeconomic policies, than the overall external events.

Originality/value

It is expected that this study has contributed to a better understanding of the volatility of interest rates and the main factors affecting this market.

Propósito

Este estudio analiza la volatilidad del mercado de renta fija de once países (Brasil, Rusia, India, China, Sudáfrica, Argentina, Chile, México, Estados Unidos, Alemania y Japón) de enero de 2000 a diciembre de 2011, mediante el examen de las tasas de interés interbancarias de cada mercado.

Diseño/metodología/enfoque

Para la volatilidad de los retornos de las tasas de interés, se utilizaron modelos de heteroscedasticidad condicional autorregresiva: ARCH, GARCH, EGARCH, TGARCH y PGARCH, y una combinación de estos con modelos ARIMA, comprobando cuáles de los procesos eran más eficientes para capturar la volatilidad de interés de cada uno de los países de la muestra.

Hallazgos

Los resultados sugieren que para la mayoría de los mercados estudiados la volatilidad es mejor modelada por procesos GARCH asimétricos —en este caso el EGARCH— demostrando que las malas noticias conducen a un mayor incremento en la volatilidad de estos mercados que las buenas noticias. Además, las causas de una mayor volatilidad parecen estar más asociadas a eventos que ocurren internamente en cada país, como cambios en las políticas macroeconómicas, que los eventos externos generales.

Originalidad/valor

Se espera que este estudio contribuya a un mejor entendimiento de la volatilidad de las tasas de interés y de los principales factores que afectan a este mercado.

Palabras clave

Ingreso fijo, Volatilidad, Países emergentes, Modelos ARCH-GARCH

Tipo de artículo

Artículo de investigación

Details

Journal of Economics, Finance and Administrative Science, vol. 22 no. 42
Type: Research Article
ISSN: 2077-1886

Keywords

Article
Publication date: 8 May 2018

Khalil Jebran

This paper aims to examine the volatility spillover dynamics between stock and foreign exchange market of China considering subprime 2007 financial crisis period.

Abstract

Purpose

This paper aims to examine the volatility spillover dynamics between stock and foreign exchange market of China considering subprime 2007 financial crisis period.

Design/methodology/approach

This study considered daily data from January 2, 2002, to December 31, 2013. The sample period has been further divided into three periods; full sample period (January 2002-December 2013), pre-crisis period (January 2002-October 2007) and post-crisis period (October 2007-December 2013). This study opted Exponential Generalized Autoregressive Heteroskedasticity (EGARCH) model for the purpose of investigating asymmetric volatility spillover.

Findings

The results obtained using the EGARCH model imply that volatility spillover dynamics varies from period to period. In full sample period, the results show evidence of significant unidirectional volatility spillover from foreign exchange market to stock market. In pre-crisis period, the results indicate unidirectional volatility spillover from stock market to foreign exchange market. However, in post-crisis period, the results reveal significant bidirectional volatility spillover between stock and foreign exchange market.

Practical implications

The results of the study are important for policy makers because understanding the behavior of the financial markets, i.e. stock and foreign exchange market, would increase the success of policies implemented in a crisis situation. The results would help investors to formulate efficient portfolios.

Originality/value

This study is an important contribution to the existing literature in terms of analyzing volatility spillover between stock and foreign exchange market in an emerging economy, China. Furthermore, this study explored the volatility spillover dynamics between the two markets by considering the pre and post subprime Asian crisis period.

Details

Journal of Asia Business Studies, vol. 12 no. 2
Type: Research Article
ISSN: 1558-7894

Keywords

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